> ## Documentation Index
> Fetch the complete documentation index at: https://phaseo.app/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# 响应

> 使用 Python SDK 调用 Responses API。

**方法**：`client.generate_response()`（使用 `client.stream_responses()` 流式传输已解析的分块）。

### 示例

```python theme={null}
resp = client.generate_response({
    "model": "openai/gpt-4.1",
    "input": [{"role": "user", "content": [{"type": "input_text", "text": "Summarise this"}]}],
    "temperature": 0.7,
})
```

### 流式传输

```python theme={null}
for chunk in client.stream_responses({
    "model": "openai/gpt-4.1",
    "input": [{"role": "user", "content": [{"type": "input_text", "text": "Stream this"}]}],
    "stream": True,
}):
    if chunk.get("text"):
        print(chunk["text"], end="", flush=True)
```

### 关键参数

* `model`（必填）：目标模型 ID。
* `input`（必填）：按顺序排列的输入项数组（消息、工具调用等）。
* `temperature`（0–2）：值越高，结果越随机。
* `top_p`（0–1）/ `top_k`（>=1）：核采样和 top-k 采样控制项。
* `max_output_tokens`（整数）：每个响应生成的 token 数上限。
* 工具：`tools`（定义）、`tool_choice`（auto/none/指定工具）、`max_tool_calls`（整数）、`parallel_tool_calls`（布尔值）。
* Logprobs：`logprobs`（布尔值）、`top_logprobs`（0–20），用于返回每个 token 的 logprobs。
* 输出：`response_format`（json/text）、`service_tier`、`store`（布尔值）、`stream`（布尔值）。
* 元数据：`metadata`（透传对象）、`reasoning`（用于提示推理强度的对象）。
* 网关扩展项：`usage`（用于请求用量的布尔值）、`meta`（用于包含 meta 块的布尔值）。

### 返回值

`ResponsesResponse`

```json theme={null}
{
  "id": "resp_123",
  "object": "response",
  "created_at": 1677652288,
  "status": "completed",
  "model": "gpt-4.1",
  "output": [
    {
      "type": "message",
      "id": "msg_123",
      "status": "completed",
      "role": "assistant",
      "content": [
        {
          "type": "output_text",
          "text": "Hello there, how may I assist you today?"
        }
      ]
    }
  ],
  "usage": {
    "input_tokens": 9,
    "output_tokens": 12,
    "total_tokens": 21
  }
}
```

`stream: true` 时以换行符分隔的 SSE 帧：

```
data: {"id":"resp_123","object":"response","created_at":1677652288,"status":"in_progress","model":"gpt-4.1","output":[{"type":"message","id":"msg_123","status":"in_progress","role":"assistant","content":[]}]}

data: {"id":"resp_123","object":"response","created_at":1677652288,"status":"in_progress","model":"gpt-4.1","output":[{"type":"message","id":"msg_123","status":"in_progress","role":"assistant","content":[{"type":"output_text","text":"Hello"}]}]}

data: {"id":"resp_123","object":"response","created_at":1677652288,"status":"completed","model":"gpt-4.1","output":[{"type":"message","id":"msg_123","status":"completed","role":"assistant","content":[{"type":"output_text","text":"Hello there, how may I assist you today?"}]}],"usage":{"input_tokens":9,"output_tokens":12,"total_tokens":21}}

data: [DONE]
```


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